Reflections on Case Studies, Modelling and Theory Building
19th International Congress on Modelling and Simulation, Perth, Australia, 12–16 December 2011 http://mssanz.org.au/modsim2011
Reflections on case studies, modelling and theory building
M. Mogliaa, K. Alexanderb, P. Perezc Affiliations: a Urban and Industrial Water Research Program, CSIRO Land and Water, Victoria, b CSIRO Ecosystem Sciences, Canberra, ACT, Australia c SMART Infrastructure Facility, University of Wollongong, New South Wales, Email: magnus.moglia@csiro.au This paper provides a discussion on how case study research fits into the bigger picture of theory building in the social sciences. In particular, it discusses how case study research, as opposed to more classical quantitative (often statistical) approaches contribute to the progression of collective learning in science. As such, for arguments sake, in this paper these approaches (i.e. qualitative vs. quantitative) are put into a competitive relationship. It is acknowledged that such competitive relationship does not exist in theory, as they are often considered to be complementary, but in practice qualitative research is often more difficult to publish; and tends to be more difficult to defend. Therefore the authors believe there is a need to better recognise the role of case study research in the scientific process; and in light of recent development in participatory modelling to collectively re-evaluate how case study research contributes to the progression of scientific learning? The deductive statistical approach in social science, as it was defined in a classic exchange of articles and ideas by mathematician Bernoulli and Galton in the 18th century is to ascertain a posteriori through knowledge based on experience, in situations when we cannot determine a “priori” (independent of experience) by statistical analysis of a number of similar instances. This assumes events in the future will follow a similar pattern as in the past, and relies on several important assumptions which may
Reflections on case studies, modelling and theory building
M. Mogliaa, K. Alexanderb, P. Perezc Affiliations: a Urban and Industrial Water Research Program, CSIRO Land and Water, Victoria, b CSIRO Ecosystem Sciences, Canberra, ACT, Australia c SMART Infrastructure Facility, University of Wollongong, New South Wales, Email: magnus.moglia@csiro.au This paper provides a discussion on how case study research fits into the bigger picture of theory building in the social sciences. In particular, it discusses how case study research, as opposed to more classical quantitative (often statistical) approaches contribute to the progression of collective learning in science. As such, for arguments sake, in this paper these approaches (i.e. qualitative vs. quantitative) are put into a competitive relationship. It is acknowledged that such competitive relationship does not exist in theory, as they are often considered to be complementary, but in practice qualitative research is often more difficult to publish; and tends to be more difficult to defend. Therefore the authors believe there is a need to better recognise the role of case study research in the scientific process; and in light of recent development in participatory modelling to collectively re-evaluate how case study research contributes to the progression of scientific learning? The deductive statistical approach in social science, as it was defined in a classic exchange of articles and ideas by mathematician Bernoulli and Galton in the 18th century is to ascertain a posteriori through knowledge based on experience, in situations when we cannot determine a “priori” (independent of experience) by statistical analysis of a number of similar instances. This assumes events in the future will follow a similar pattern as in the past, and relies on several important assumptions which may
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